title: Global exponential stability of interval general BAM neural networks with reaction-diffusion terms and multiple time-varying delays.
abstract: In this paper, we first discuss the existence and uniqueness of the equilibrium point of interval general BAM neural networks with reaction-diffusion terms and multiple time-varying delays by means of using degree theory. Then by applying the existence result of an equilibrium point and constructing a Lyapunov functional, we discuss global exponential stability for above neural networks. In the last section, we also give an example to demonstrate the validity of our global exponential stability result for above neural network.
authors.affiliation: College of Mathematics, Hunan University, Changsha 410082, PR China. zhangzhengqiu@hnu.cn
authors.forename: Zhengqiu
authors.initials: Z
authors.lastname: Zhang
authors.forename: Yan
authors.initials: Y
authors.lastname: Yang
authors.forename: Yesheng
authors.initials: Y
authors.lastname: Huang
mesh_terms: D001185:Artificial Intelligence; D003198:Computer Simulation / Q000592:standards*; D004058:Diffusion; D006801:Humans; D055641:Mathematical Concepts; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D011930:Reaction Time / Q000502:physiology; D015203:Reproducibility of Results; D013997:Time Factors